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Why Python in Penetration Testing?

In this chapter, we will cover the following recipes:

Why Python is a great option for security scripting
Python 3 language basics and differences

Why Python is a great option for security scripting

In the wake of big security attacks and breaches, security/penetration testing is gaining momentum in the quality field. As a popular language in the programming area, it is evident from the tools, books, and scripts published in the last couple of years that Python has become the favorite scripting language for security researchers and hackers.

Getting ready

Even though network and application security is inundated with many tools for automated and semi-automated tests, it may not always guarantee success. Improvisation of tools and scripts is the key to pen-testing, and there will always be some tasks that demand to be automated or to be fulfilled in another way. Becoming a successful real-world penetration tester involves a lot of custom scripting and programming tasks.

How to do it...

These are the main reasons for Python's popularity in security scripting and programming.

Python can be used in both and interpreted and compiled forms

Python programs can be compiled in any situation where they can be used as compiled and not required frequent changes. This will make Python programs run much faster and provide a better opportunity to remove vulnerabilities and bugs. Also, interpreted programs run much slower than compiled programs, and are more prone to vulnerabilities and attacks.

Python code uses no compiler and can run on just about any device that runs the Python shell. Also, it shares a couple of other resemblances to scripting languages over programming languages. So, Python can be used to perform the functions of a scripting language.

Syntax and indented layout

The syntax and indented layout of Python makes it easy to figure out what is happening in a program during the review. The indentation also makes the program more readable and helps make the collaborative programming easier.

Simple learning curve

Learning a new programming language is always a rigorous task. But Python was designed in such a way that it should be easily learned by even a novice programmer. Python's growing acceptance with the programmers is mainly due to its easiness to learn and its design philosophy highlights code readability that will help the beginner developers to learn many things by reading the code itself. Also, Python's read evaluate print loop (REPL) provides the developer a chance to play around with code and experiment with it. The standard Python library maintains a lot of functionalities with which we can execute complex functionalities with ease.

Powerful third-party libraries

Once you have learned Python, you can leverage the platform backed with a large number of libraries. The Python Package Index (PyPI), is a repository of more than 85,000 reusable Python modules and scripts that you can use in your scripts. Python is the best language to learn as a security researcher, because of the availability of its large number of reverse engineering and exploitation libraries.

Cross-platform (code anywhere)

Python works on Linux, Microsoft Windows, macOS X, and many other operating systems and devices. A Python program written on a macOS X computer will run on a Linux system and vice versa. Also, Python programs can run on Microsoft Windows computers, as long as the machine has Python interpreter installed.

Python 3 language basics and differences

Python 3.0 was first released in 2008. Even though Python 3 supposed to be backward incompatible with other old version, many of its features are backported to support older versions. It is better to have an idea of Python versions and its differences for better understanding of our recipes.

Getting ready

If you are new to Python, you might be confused about the different versions that are available. Before looking into the further details, let's have a look at the most recent major releases of Python and the key differences between Python 2 and Python 3.

How to do it...

These are the major Python versions available.

Python 2

Published in late 2000, it has many more programmatic features including a cycle-detecting garbage collector that helps to automate memory management. The increased unicode support that helps to standardize characters, and list comprehensions that help to create a list based on existing lists are other features. In Python version 2.2, the types and classes are consolidated into one hierarchy.

Python 3

Python 3 was released in late 2008, to update and fix the built-in design flaws of the prior versions of Python. The main focus of Python 3 development was to clean up the code base and reduce redundancy.

In the beginning, the adoption of Python 3 was a very slow process due to its backward incompatibility with Python 2. Moreover, many package libraries were only available for Python 2. Later, there was an increased adoption for Python 3 as the development team announced that there will be an end of life for Python 2 support and more libraries have been ported or migrated to Python 3.

Python 2.7

Python 2.7 was published in 2010 and was planned as the last release for 2.x versions. Its intention was to make it easier for Python 2.x users to port their features and libraries over to Python 3 by providing compatibility between the two, which included a unit test to support test automation, argparse for parsing command-line options, and more convenient classes in collections.

Key differences between Python 2.7 and Python 3

Here are some main differences between Python 2.x and Python 3:

Print: In Python 2, print is a statement. So, there is no need to wrap the text in parentheses for printing. But in Python 3 print is a function. So, you have to pass the string you need to print to the function in parentheses.
Integer division: Python 2 considers numbers without any digits after the decimal point as integers, which may lead to some unexpected results during division.
List comprehension loop variables leak: In Python 2, giving the variable that is iterated over in a list comprehension leaks the variable into surrounding scope, this list comprehension loop variable leak bug has been fixed in Python 3.
Unicode strings: Python 2 requires you to mark the unicode string explicitly with the u prefix. But, Python 3 stores strings as unicode by default.
Raising exceptions: Python 3 requires different syntax for raising exceptions.

The progression from Python 2.x to Python 3.x is happening slowly, but it is underway. It is good to be mindful that there are material differences between Python 2.x and Python 3 as you may need to deal with code that is written in the version with which you are less familiar.

Key benefits

Learn to detect and avoid various types of attack that put system privacy at risk

Enhance your knowledge of wireless application concepts and information gathering through practical recipes

Learn a pragmatic way to penetration-test using Python, build efficient code, and save time

Description

Penetration testing is the use of tools and code to attack a system in order to assess its vulnerabilities to external threats. Python allows pen testers to create their own tools. Since Python is a highly valued pen-testing language, there are many native libraries and Python bindings available specifically for pen-testing tasks. Python Penetration Testing Cookbook begins by teaching you how to extract information from web pages. You will learn how to build an intrusion detection system using network sniffing techniques. Next, you will find out how to scan your networks to ensure performance and quality, and how to carry out wireless pen testing on your network to avoid cyber attacks. After that, we’ll discuss the different kinds of network attack. Next, you’ll get to grips with designing your own torrent detection program. We’ll take you through common vulnerability scenarios and then cover buffer overflow exploitation so you can detect insecure coding. Finally, you’ll master PE code injection methods to safeguard your network.

What you will learn

•Learn to configure Python in different environment setups.

•Find an IP address from a web page using BeautifulSoup and Scrapy

•Discover different types of packet sniffing script to sniff network packets

•Master layer-2 and TCP/ IP attacks

•Master techniques for exploit development for Windows and Linux

•Incorporate various network- and packet-sniffing techniques using Raw sockets and Scrapy

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Paperback book shipped to your preferred address

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Frequently bought together

Python: Penetration Testing for Developers

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Muneeb Dec 20, 2017

Covers most of the penetration testing scenarios. A lot of out of the box pen testing recipes.

Amazon Verified review

Amazon Customer Apr 26, 2023

Only 205 pages (vs 728).Not with the price tag in my opinion.

Piehole Willie Aug 04, 2020

It's like if you already know how to grill a steak… and you already know how to boil a lobster… then someone sells you a book on how to make a new dish called “surf & turf”. Book assumes you know pen testing. And assumes you know Python. So here’s a quick few pages on how to do some pen test tricks in Python!Here are my issues with this book (I bought the Kindle edition yesterday and finished it already): (1) its pretty short at 206 total pages, with way too many of those few pages spent on preface, intro, table of contents, setting up Python…. I didn't even get the first pen test topic until 21% into the book. Not a lot of substance here. (2) Its a sampling of a few pen test topics, not, in my opinion, a reasonably comprehensive “cookbook”. (3) The pen test tasks/concepts the recipes are intended to solve for are barely described. For example, the concept of IP Spoofing is described in literally just two sentences before diving into the code example. (4) The code examples are all about “what” and not about “why”. “Import these modules, declare these variables, type this function, then run the script!” No explanation at all about the modules themselves, no explanation of the Python code samples to help you understand why it works, no point of view around how this code would be used in the context of an actual pen test.I had high hopes for this. I’m a big fan of Packt, and I own and recommend many of their titles. But I didn’t get much value out of this one.

Python Penetration Testing Cookbook: Practical recipes on implementing information gathering, network security, intrusion detection, and post-exploitation

What do you get with Print?

Python Penetration Testing Cookbook

Why Python in Penetration Testing?

Introduction

Why Python is a great option for security scripting

Getting ready

How to do it...

Python can be used in both and interpreted and compiled forms

Syntax and indented layout

Simple learning curve

Powerful third-party libraries

Cross-platform (code anywhere)

Python 3 language basics and differences

Getting ready

How to do it...

Python 2

Python 3

Python 2.7

Key differences between Python 2.7 and Python 3

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Python Penetration Testing Cookbook: Practical recipes on implementing information gathering, network security, intrusion detection, and post-exploitation

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Description

Who is this book for?

What you will learn

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What do you get with Print?

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Table of Contents

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